Tommaso Cesari

Tommaso Cesari serves as an Assistant Professor in the EECS department at the University of Ottawa, cross-appointed with the Department of Mathematics and Statistics. He currently teaches Machine Learning (CSI 4145) and Introduction to Computing II (ITI 1121 A), courses he has instructed since 2024 and 2023 respectively.

His research centers on theoretical machine learning with applications in market design and operational systems. Key interests include online learning frameworks for bandit problems, pricing mechanisms, bilateral trade optimization, and spacecraft operations scheduling. This work bridges algorithmic theory with real-world economic systems, emphasizing regret minimization under adversarial conditions and smoothed analysis.

Analysis of his 2023-2025 publications reveals a cohesive trajectory in applying online learning to bilateral trade mechanisms (appearing in 7 of 15 recent papers), auction theory, and brokerage models. His work consistently targets top venues including JMLR, NeurIPS, and STOC, with growing emphasis on fairness constraints and multi-platform systems in 2024-2025 outputs.

Professor Cesari actively recruits Master's and Ph.D. students for research in his domains; prospective candidates may apply through the university portal. His collaborative publications with prominent researchers like Nicolò Cesa-Bianchi indicate strong engagement in the theoretical machine learning community.